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    <titleInfo>
        <title>Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression</title>
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    <name type="personal">
        <namePart type="given">Terra</namePart>
        <namePart type="family">Blevins</namePart>
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    <name type="personal">
        <namePart type="given">Robert</namePart>
        <namePart type="family">Kwiatkowski</namePart>
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    <name type="personal">
        <namePart type="given">Jamie</namePart>
        <namePart type="family">MacBeth</namePart>
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    <name type="personal">
        <namePart type="given">Kathleen</namePart>
        <namePart type="family">McKeown</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Desmond</namePart>
        <namePart type="family">Patton</namePart>
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    <name type="personal">
        <namePart type="given">Owen</namePart>
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            <title>Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</title>
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        <name type="personal">
            <namePart type="given">Yuji</namePart>
            <namePart type="family">Matsumoto</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Rashmi</namePart>
            <namePart type="family">Prasad</namePart>
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    <abstract>Violence is a serious problems for cities like Chicago and has been exacerbated by the use of social media by gang-involved youths for taunting rival gangs. We present a corpus of tweets from a young and powerful female gang member and her communicators, which we have annotated with discourse intention, using a deep read to understand how and what triggered conversations to escalate into aggression. We use this corpus to develop a part-of-speech tagger and phrase table for the variant of English that is used and a classifier for identifying tweets that express grieving and aggression.</abstract>
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        <url>https://aclanthology.org/C16-1207</url>
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        <date>2016-12</date>
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            <start>2196</start>
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%0 Conference Proceedings
%T Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression
%A Blevins, Terra
%A Kwiatkowski, Robert
%A MacBeth, Jamie
%A McKeown, Kathleen
%A Patton, Desmond
%A Rambow, Owen
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F blevins-etal-2016-automatically
%X Violence is a serious problems for cities like Chicago and has been exacerbated by the use of social media by gang-involved youths for taunting rival gangs. We present a corpus of tweets from a young and powerful female gang member and her communicators, which we have annotated with discourse intention, using a deep read to understand how and what triggered conversations to escalate into aggression. We use this corpus to develop a part-of-speech tagger and phrase table for the variant of English that is used and a classifier for identifying tweets that express grieving and aggression.
%U https://aclanthology.org/C16-1207
%P 2196-2206

Markdown (Informal)

[Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression](https://aclanthology.org/C16-1207) (Blevins et al., COLING 2016)

• Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression (Blevins et al., COLING 2016)

ACL

• Terra Blevins, Robert Kwiatkowski, Jamie MacBeth, Kathleen McKeown, Desmond Patton, and Owen Rambow. 2016. Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 2196–2206, Osaka, Japan. The COLING 2016 Organizing Committee.